More Information
We will run this course in person in Cambridge on Tuesday February 9th and Wednesday February 10th 2027. As this is the first iteration of the course, we are offering participants the opportunity to take part at an introductory price. A further discount is available if participants provide written feedback on the course, and at least one chapter from a book in development which covers the course material.
The course price is £300, discounted to £200 if participants provide written feedback on the course plus one chapter. This covers refreshments, lunch, and an optional dinner on Day 1. Participation will be limited to the first 25 registrations.
Course tutors:
Stephen Burgess, Research Professor in Biostatistics, University of Cambridge
Nasir Bashir, Wellcome Trust PhD Fellow, University of Cambridge
Jeremy Labrecque, Assistant Professor of Epidemiology and Leader of the Causal Inference Group at Erasmus MC, Rotterdam, the Netherlands
Emily Bassett, Research Associate, University of Cambridge
Intended audience:
The course is written for participants working in epidemiology, public health, healthcare policy, evidence-based medicine, or health data science, who want to understand how causal claims are determined and evaluated. While examples will focus on epidemiology, the material will be broadly accessible to anyone working in the social sciences. The course will be particularly suitable for PhD students and early-career researchers both in academia, government, and industry.
Prerequisites:
Familiarity with epidemiological terminology and concepts will be helpful, but no specific epidemiological, biological, or clinical knowledge is needed. We will assume a base level of familiarity with statistical methods: previous experience of linear regression would be sufficient.
Computing practicals:
No prior background in programming is assumed. For the computer practical, full worked example code in the R programming language will be provided. Confident participants can attempt the questions and check their answers against the example code. Newcomers can copy-and-paste code to see the output, so that they can focus on implementing the method and interpreting its output.
Course objectives:
After the course, participants should be able to understand some of the core principles of causal inference, to apply these principles to the design and analysis of data, and to critically appraise approaches to causal inference in epidemiology.
Software download: Details of software to be downloaded for use on the course practicals will be given to course participants. Please do not worry if there are any problems with the software, as there will be an opportunity for installation during the course.
For further course details or information please visit https://mendelianrandomization.com/courses-overview/
For answers to course queries, please email burgess-group-admin@mrc-bsu.cam.ac.uk
Cancellation Policy
Full refunds will be given for cancellation 28 or more working days before the course start date. Otherwise the full course fee will be charged. However, registrations may be transferable to another course or individual.
In the unlikely event that the short course has to be cancelled, our liability is limited to refund of course fees only.
Please visit https://www.medschl.cam.ac.uk/institutions/mrc-bsu/short-courses-mrc-biostatistics-unit
